Senior Software Engineer, Platform
About this role
Scale AI needs a technical leader to build and evolve the core orchestration platform that runs durable, reliable, and scalable workflows across the entire organization. The platform powers complex, long-running processes ranging from data and model-evaluation pipelines to operational systems and customer-facing workflows, requiring robust underlying infrastructure.
Working directly on this infrastructure involves designing primitives, services, and developer experiences that allow internal teams to author, operate, observe, and safely scale distributed workflows. Engineers who enjoy backend infrastructure, distributed systems reliability, and platform engineering will thrive in this environment.
Collaboration is central to the position, as the team partners closely with product, infrastructure, data, and application units to turn workflow needs into reusable platform capabilities. Candidates with a strong background in backend systems and distributed architecture are well-positioned to drive these technical standards forward.
What you will do
- Lead the architecture, design, implementation, and operation of Scale's core orchestration platform.
- Build durable workflow infrastructure using technologies like Temporal, Cadence, Kubernetes, and cloud-native systems.
- Define platform primitives and APIs for scheduling, retries, state management, task execution, observability, and workflow lifecycle management.
- Partner with product, infrastructure, data, and application teams to understand workflow needs and translate them into reusable platform capabilities.
- Improve the reliability, scalability, security, and developer experience of services running critical company workflows.
- Establish technical standards and best practices for distributed workflow development, deployment, testing, and incident response.
- Drive cross-functional technical decisions and communicate platform direction clearly to engineers and stakeholders.
What you need
- Bring five or more years of full-time software engineering experience with a focus on backend, infrastructure, and distributed systems.
- Demonstrate experience building and operating production systems with strong requirements for reliability, availability, and scale.
- Possess deep familiarity with workflow orchestration platforms such as Temporal, Cadence, AWS Step Functions, or Kubernetes.
- Have deep familiarity with Kubernetes and containerized production environments alongside working knowledge of Terraform and Docker.
- Demonstrate strong knowledge of distributed-systems concepts including asynchronous execution, retries, idempotency, fault tolerance, state management, and observability.
- Show a track record of leading technically complex projects from initial design through rollout and ongoing operation.
- Exhibit excellent communication skills to collaborate effectively with platform consumers and non-technical stakeholders.
Nice to have
- Experience with data warehouses such as Snowflake and Firebolt, as well as data pipeline and ETL tools like Dagster and dbt
- Experience with authentication and authorization systems like Zanzibar and Authz
- Experience scaling products at hyper-growth startups
- Excitement to work with AI technologies
Benefits
- Comprehensive health, dental, and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous PTO
- Commuter stipend
Skills and tech stack
Questions candidates ask
Where is this role located?
This position is located in San Francisco, CA and New York, NY, with the base salary range also applicable for Seattle.
What is the compensation range for the position?
The base salary range for this full-time position in San Francisco, New York, and Seattle is $216,000 to $270,000 USD. Eligible roles also receive equity-based compensation subject to Board of Director approval.
What benefits are included?
Employees receive comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, generous PTO, and potentially a commuter stipend.
What is the policy for reapplying if I am not selected?
Company policy requires a 90-day waiting period before reconsidering candidates for the same role to ensure a fair and thorough evaluation of all applicants.